hoseo_lms

What This Skill Does

The hoseo_lms skill is a powerful data aggregation and management tool designed specifically for students at Hoseo University using the university's Learning Management System (LMS). This tool functions as a local dashboard, allowing you to centralize your academic information without needing to navigate the complex web interface of the official portal manually. It provides three core utilities: data scraping to pull course metadata, an automated summary report generator, and a structured video playback utility. By fetching information on assignments, quiz deadlines, and lecture progress, it helps students keep a bird's-eye view of their academic workload. Most importantly, the tool is strictly read-only and user-initiated; it does not perform automated grade modifications or unauthorized attendance submissions.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/acogkr/hoseo-lms

Ensure that you have Python 3 installed on your system, as the skill operates by calling local Python scripts directly from the source repository provided by the author, acogkr.

Use Cases

This skill is perfect for students looking to improve their time management. You can use it to generate a clean, text-based dashboard that displays all pending assignments and upcoming quiz dates across multiple courses simultaneously. Additionally, the auto_attend module is ideal for users who want to streamline their lecture viewing process by defining specific lecture counts or week ranges, ensuring you never miss a video requirement while keeping your progress transparent.

Example Prompts

1. "OpenClaw, run the scraper and show me my current pending assignments for this week."
2. "Use the auto_attend utility to play the next 3 videos for my Database course."
3. "Summarize all my upcoming deadlines and lecture requirements into a quick report."

Tips & Limitations

To maximize the utility of hoseo_lms, always ensure your credentials.json is configured correctly so the scraper can access your course pages. Note that this is a local tool; it only reads public-facing LMS pages and does not automate submission processes. Avoid running high-frequency requests to prevent potential rate-limiting by university servers. Keep your environment updated regularly to ensure compatibility with any changes in the LMS front-end layout.